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Full text of "Budgetary participation, motivation and managerial performance"



WORKING PAPER 
ALFRED P. SLOAN SCHOOL OF MANAGEMENT 



BUDGETARY PARTICIPATION, MOTIVATION 
AND 
MANAGERIAL PERFORMANCE 



by 



WP 1389-83 



Peter Brownell 

and 

J. Morris Mclnnes 



January 1983 



MASSACHUSETTS 

INSTITUTE OF TECHNOLOGY 

50 MEMORIAL DRIVE 

CAMBRIDGE, MASSACHUSETTS 02139 



BUDGETARY PARTICIPATION, MOTIVATION 
AND 
MANAGERIAL PERFORMANCE 

by 

Peter Brownell 
and 
J. Morris Mclnnes 
WP 1389-83 January 1983 



Abstract 

The paper proposes an "indirect-effects" model linking participation in 
budget-setting with managerial performance. Motivation was selected as an 
intervening variable to explore the proposed model in a field study 
setting. A significant positive association between participation and 
performance was observed. However, the indirect path linking participation 
and performance through motivation was found to explain only a small amount 
of the relationship. In the study, motivation was measured using an 
expectancy model. Further analysis revealed that greater participation in 
budget-setting was positively associated with the extrinsic components of 
motivation, but negatively with the intrinsic components. Contrary to 
wide-held beliefs, the results seemed to suggest that participation 
reinforces the contractual nature of the budget at the expense of the 
personal satisfactions derived from goal-directed behavior and 
goal-accomplishment. The managerial implications of the "indirect-effects" 
model, and of the findings of the study, are discussed in the final section 
of the paper. 



Budgetary Participation, Motivation And Managerial Performance 

Early theorists (e.g., Argyris, 1952; Becker and Green, 1962) tended to 
the view that participation in the budget-setting process was a major means 
available to organizations to gain the commitment of managers to budgets, 
with consequent improvement in performance. Hopwood (1976) summarized this 
earlier sentiment when he suggested that participation was viewed by many as 
"...a panacea: a cure for all the many ills which have been associated with 
traditional Dudgetary systems" (p. 74). Nonetheless, even in the 
non-empirical realm in which much of this debate was conducted disagreement 
was evident. The reply to Becker and Green by Stedry (1964), together with 
Becker and Green's (19o4) rejoinder, illustrates the controversial nature of 
the debate. 

As subsequent empirical evidence accumulated, it became clear that these 
earlier disagreements were well founded, l^ile evidence emerged of positive 
relationships between participation and criteria such as job satisfaction 
(Cherrington and Cherrington, 1973), attitude towards job (Milani, 1975), 
motivation (Hofstede, 1967; Searfoss and Monczka, 1973), and attitude 
towards the budget system (Collins, 1973; Kenis, 1979), no consistent 
relationship with performance was found. 

A possible explanation for the lack of an observed association between 
participation and performance revolves around the role of moderating 
variables, that is, variables which interact with participation jointly to 
affect performance. This view gained formal recognition in the literature 
with the emergence of the contingency framework for control system design 
(see, for example, Waterhouse and Tiessen, 1978; Otley, 1980). Specifically 
with regard to participation, Brownell (1982a) has reviewed and synthesized 
the literature within a framework which explicitly provides for interactive 



effects of participation with organizational, interpersonal, and individual 
variables. Recent empirical work (Brownell 1981, 1982b) has produced 
results consistent with this "moderated-ef f ects" framework. 

A second possible explanation, and the one pursued in this paper, 
emerges from literature in organizational behavior. In a review of 
literature in the area of goal setting and routine task performance, Locke 
and Schweiger (1979) could find no evidence of a systematic association 
between participation and performance. Locke, et. al. (1981, p. 138) went 
on to propose that to the extent it is found to be associated with 
performance, participation may be influencing this through the joint 
mechanisms of inducing higher goals and enhanced goal-commitment on the part 
of workers. In other words, these authors imply an "indirect-effects" model 
in which some other condition, aroused by participation, is positively 
associated with performance. 

The difference between the "moderated-ef f ects" and "indirect-effects" 
frameworks is significant, and deserves brief elaboration. The "moderated- 
effects" model posits the existence of variables which may interact with 
participation to affect performance; but these variables are viewed as 
neither directly affecting performance, nor being affected by 
participation. To illustrate, Brownell (1981) found that the individual 
variable, internal/external locus of control , interacted with 
participation to affect performance. Internals were found to prefer, and 
perform better, under conditions of high participation while externals 
preferred, and performed better, under low participation conditions. 
However, participation and locus of control were themselves unrelated, and 
no effects of the latter on performance were found. By contrast, the 
"indirect-effects" model posits the existence of variables which are 
associated with participation and which, in turn, affect performance. In 

-2- 



this framework, it is possible that statistically significant associations 
between participation and some intervening variable on the one hand, and 
between the intervening variable and performance on the other, could combine 
in such a way as to yield an insignificant association between participation 
and performance. 

In this study, motivation was chosen as an intervening variable in an 

2 
empirical investigation of the indirect-effects model. Apart from the 

intuitive plausibility of motivation as an intervening variable, there is 

ample justification in the literature for its choice. This is dealt with in 

the next section of the paper. 

Review of Previous Literature 

Hofstede (1967), in his seminal study of budgeting, observed that, "Of 
all variables studied, budget participation is the one with the strongest 
effect on all measures of motivation" (pp. 181-182). Hofstede used four 
measures of motivation, dealing with the perceived relevance of the budget 
and the existence of favorable attitudes towards the budget on the part of 
budgeted managers. Similar results were found by Searfoss and Monczka 
(1973) who studied the effects on motivation of participation by general 
foremen in the development of their budgets; motivation was measured through 
the use of subordinates' ratings of the level of effort expended by the 
foremen in goal-directing and evaluative activities based on the budget. 

In both these studies the concept of motivation was operationalized in 
terms' of acceptance of, and effort expended to achieve the budget. In this 
study motivation is operationazlied by use of the expectancy model (see, for 
example, Galbraith and Cummings [1967], House [1971], and Ronen and 
Livingstone [1975]). The model, shown in Equation (1), is considerably more 
general in its interpretation of motivation than the constructs used by 
Hofstede and by Searfoss and Monczka. It posits that individuals will exert 

-3- 



Equation 1 



Expectancy Model of Motivation: 



n 

M = IV, + P, (IV +1 P„. EV.) 
b 1 a . , 2i 1 
1=1 

Where: M is motivation 

Ivjj is the intrinsic valence associated with 
goal-directed behavior 

Px is the instrumentality, or probability, that 
goal-directed behavior will result in goal accomplishment 

IV^ is the intrinsic valence associated with goal accom- 
plishment 

P2i is the expectation, or probability, that goal accom- 
plishment will result in the ith extrinsic outcome, 
i = 1, ,n. 

EVi is the valence of the ith extrinsic outcome, 
i = 1, , n. 



effort towards goal achievement to the extent that such effort is perceived 
likely to be instrumental in achieving the goal, and additionally, to the 
extent that positively valent (desirable) outcomes are perceived likely to 
result from goal-directed behavior and from goal-achievement. 

The intrinsic valences, or rewards, arise from within the individual - 
essentially the personal satisfactions derived from goal-directed behavior and 
goal-accomplishment. The extrinsic valences are proferred by some agent 
external to the individual, such as the organization (e.g. additional pay, 
promotion, etc.), peers, subordinates, or parties outside the organization. 

Some possible effects of budgetary participation on the elements of the 
expectancy model have been suggested by Ronen and Livingstone (1975). They 
speculate, for example, that ego-involvement associated with pursuing a 



-4- 



self-set goal will enhance IV , and possibly also IV, . To the extent this 
is true, however, attendant adverse conseqences for the EV's may arise, 
following from attribution theory (see, for example, Staw, [1980] and 
Kruglanski 11978]), which posits that extrinsic and intrinsic rewards are in 
some state of psychological balance in respect to an individual's 
self-perception. In other words, a strengthening of the attribution of effort 
to the receipt of intrinsic rewards is a possible consequence of the removal 
or reduction of extrinsic rewards, and vice versa. 

A relationship of participation with P is also likely. Raia (1965) has 
suggested that more difficult goals emerge from participative budgeting. This 
might translate into reduced perceptions of P , but might increase IV^ due 
to the enhanced internalized value of achieving more difficult goals (Locke 
et. al., 1981, pp. 127 - 129). 

How, or whether these opposing tendencies balance out in their effects on 
LDotivation is unclear. Overall, however, an assessment of the possible 
effects of participation suggests that there are more opportunities for 
enhancing than for diminishing motivation. This judgment is consistent with 
the empirical findings referred to earlier. 

Turning to a consideration of the effects of motivation on performance, 
this question is dealt with largely within the domain of organizational 
behavior. Nevertheless, in the accounting literature some attention has 
recently been given to the issue (Ferris, 1977; Rockness, 1977). Ferris, 
using a relatively simple construction of motivation, found inconclusive 
results regarding the association between motivation and performance. On the 
other hand, Rockness, in an experimental study, and using a more complex 
formulation of the expectancy model, found relatively strong support for a 
positive relationship. 

In the organizational behavior area, much of the research examining the 

-5- 



relationship between motivation and performance stems from the work of Porter 
and Lawler (1968). They posit that motivation should contribute to an 
explanation of performance and also, under specified conditions, to job 
satisfaction. A great deal of subsequent research has been conducted and is 
summarized in several review articles (Mitchell, 1974; Wahba and House, 1974; 
Connolly, 1970). llitchell (1979) concludes that most of the research results 
support a positive relationship between motivation and performance. 

Method 

Data for the study were collected by a survey questionnaire from 224 
middle-level managers drawn from three separate companies - two in the 
electronics industry and one in the steel industry. The managers held 
positions in a variety of functions, including marketing, production, 
research, and administration. One selection criterion was used, namely that 
activities of the managers should be controlled, at least in part, via the use 
of budgeting. Final sample selection was left to top management of each 
company; thus the sample was not strictly random. 

The questionnaire measured participation in budget-setting, motivation and 
performance. 

Budgetary Participation 

The participation measures developed by Milani (1975) and by Hofstede 
(1967) were both employed in this study. The Milani measure is a six item 
Likert type scale, each item calling for a response from one to seven. The 
scale is designed for an additive construction of the overall score, and a 
previously performed factor analysis of the scale (Brownell, 1982b) provides 
adequate confirmation of the single factor nature of the measure. The 
Cronbach alpha reliability coefficient computed from its use in this study 

-6- 



was 0.76. 

The Hofstede measure is an eight-point, single-choice scale, with full 
verbal anchoring. It was used in this study simply to validate the Milani 
measure, with which it correlated at 0.59 (p<O.Ol), 

Motivation 

The questionnaire items were designed to elicit measures on each construct 
of the model presented in Equation (1). In the following discussion, we first 
address valences, and then instrumentalities/expectancies. 

Valences: The approach to the measurement of the valences was adapted 

from the procedure developed by Lawler and Suttle (1973) in such a way as to 

distinguish between the three classes of valence (IV,, IV , and EV's). 

b a 

Seventeen outcomes were used, classified a priori as either intrinsic (eight 
outcomes) or extrinsic (nine outcomes). The outcomes are listed in Appendix 

A. For each outcome, respondents were twice asked to indicate on a scale from 

3 

one to nine (extremely desirable to extremely undesirable) the strength of 

their preference for that outcome. First respondents were asked to value each 
outcome as it might result from "working hard" (goal-directed behavior), and 
then to value each outcome as it might arise from "meeting or beating budgeted 
goals" (goal-accomplisl"UDent) . IV, was measured by averaging the eight 
responses to the intrinsic items from the first set of responses. IV was 
measured by averaging the responses to the same eight items, but from the 
second set of responses. The use of the same eight intrinsic outcomes in the 
measurement of IV, and IV pre-supposes that a given outcome may arise 
from either goal-directed behavior or goal-accomplishment; and moreover, that 
the value placed on it might vary depending on how it arises. 

The valences associated with the nine extrinsic outcomes (EV's) were 
assessed from the second set of responses (outcomes resulting from 

-7- 



feoal-accomplishment) • 

Instrumentalities/Expectancies: Equation (1) requires the assessment of 
nine specific instrumentalities associating goal-accomplishment with extrinsic 
outcome (Pn's). These instrumentalities were assessed by asking respondents 
to indicate on a scale from one (never) to seven (always), how often "meeting 
or beating the budget" would result in each outcome. Three additional 
questionnaire items elicited measures of P-, , the perceived probability that 
goal-directed behavior would result in goal-accomplishment. For ease of 
interpretation, the instrumentality responses were converted to probabilities 
in the range of zero to one. The three assessments of P, were significantly 
(p < 0.01) correlated, with a mean correlation of 0.35. A single measure of 
P, was derived by averaging the three responses. 

The final measure of motivation was then obtained by aggregating the 
individual constructs following Equation (1). 

Performance 

A self-rating version of the performance measure developed by Mahoney 
et.al. (1963, 1965) was used. The measure calls for ratings on a nine-point 
scale for each of eight separate dimensions of performance , together with a 
single overall rating. In developmental work, Mahoney et al. (1963 pp. 
106-107) indicated that the eight separate dimensions were conceived of as 
being independent, and that jointly, the dimensions should explain at least 55 
per cent of the overall rating (the remainder being explained by job-specific 
factors). Each of these claims was tested in the current study. To assess 
dimensional independence, a rule of thumb suggested by Pindyck and Rubinfeld 
(1976, p. 68) was used. Multi-collinearity among an independent variable set 
is likely to be a concern if the sample correlation between two of the 
independent variables (dimensions) is larger than the correlation of either or 

-8- 



both with the dependent variable (in this case, the overall rating). Of 28 
possible comparisons, only three intercorrelations violated this criterion, 
indicating that the eight dimensions are reasonably independent. To test the 
second claim, the overall performance rating was regressed on the eight 
sub-dimensions. The regression explained 78 percent of the variance in the 
overall ratings, implying that only 22 per cent of the functions critical to 
effective performance were job-specific in the current sample. 

Approach to Anal ysis 

Because of the hypothesized collinearity between participation and 
motivation, ordinary multiple regression cannot be used in the analysis. 
Instead, partial regression, in the spirit of path analysis, was used. The 
major benefit of path analysis is that it allows a decomposition of the 
relationship between two variables in a structural model into the direct 
effects of one on the other, as well as the indirect effects of the first on 
the second, via one or more intervening variables. 

The basic form of the structural model hypothesized earlier is depicted 
in Figure 1, where participation, the exogenous variable in the model, is 
denoted as X, , motivation as X~, and performance as X^. The path 
coefficients in the model are denoted p. ., and R, denotes the 
unexplained portions of the endogenous variables, motivation and performance. 



-9- 




Figure 1: Structural Model 



The equations to the structural model are as follows; 



Xo = 



^21 1 '^Zu u 



(2) 



X. = 



p^^X + p^„X + p R 
31 1 32 2 ^3v V 



(3) 



The solution for p„ , can be directly assessed by computing the 
correlation ^-i^' A path coefficient between two variables will equal the 
zero-order correlation between them in circumstances where a variable is 
viewed to be dependent on a single cause and a residual. This is true for 
X (motivation) which, in the model, is conceived of as being dependent 
only on X, (participation). 

The solutions to p^^ ^"^"^ Pin ^^^ ^^ obtained in several equivalent 
ways. One possibility (Stokes, 1974) is by means of an instrumental 
variable procedure. This involves multiplying equations by suitable 



-10- 



instruments, taking expected values, and solving. Suitable instruments are 
variables contained in a particular equation which are uncorrelated with the 
residual variable of that equation. In equation (3), for example, X and 
X^ are suitable, but X-, is not. 

A second approach, and the one used here, involves partial regression. 
If, as above, it is assumed that the residuals are uncorrelated with the 
explanatory variables in the equations in which they appear, and all 
variables are expressed in standard form, then the p. .'s can be estimated 
by ordinary least squares procedures; they are in fact equal to the 
standardized partial regression coefficients. Equations (2) and (3) can be 
rewritten as follows: 

^2 = e2iX^ + P2, R, (4) 

^3= ^31.2^1^^32. 1^2 +P3v^ ^^^ 

The residual path coefficients can be calculated using the general form: 

p. = / (1 - r^) 
le e 

2 
where r is the square of the appropriate multiple correlation 

coefficient. In the present context, we have: 

P2u = ^ ^^ - ^12^ (^) 

P3v - •/ ^1 - ^3.12) <7) 

Finally, the decomposition of the total effect of one variable in the 

model on another is obtained using the computed path coefficients and 
zero-order correlations: 

^12 = P2I ^8) 

rj_3 = P31 + P32ri2 (9) 

r23 = P32 + P3;l^12 ^l^^ 

-11- 



The second components on the right hand side of equations (9) and (10) 
capture the indirect effects, while the first components, the path 
coefficients themselves, capture the direct effects. 



Results 

Of 224 questionnaires distributed, 140 were returned, a response rate of 
02.5%. Of the 140 returned questionnaires 32 were excluded because of 
improper or incomplete responses. The final sample size was therefore 108. 

The zero order correlations among the three variables, participation, 
motivation, and performance, are shown in Table 1. The probabilities 
reported in Table 1 are based on a two-tailed test, as are all the other 
results presented in the paper. 



INSERT TABLE 1 HERE 



The set of path coefficients of equation (3) were computed following 
the procedure outlined in the previous section. The approach involves 
regressing X on X and X in a multiple regression in which all 
variables are standardized. The coefficient on X is p^, , and on X„ 
is P32* The results of the regression are presented in Table 2. Both 
path coefficients, and the overall regression itself, are positive and 
significant. 



INSERT TABLE 2 HERE 



-12- 



The path coefficients for the errors in Figure 1 are derived by the 

application of the formulae in Equations (6) and (7) to the results obtained: 

p., = 0.990 
2u 

P3^ = U.984 

Finally, the decomposition of total effects within the model presented 
in Figure 1 is performed following Equations (9) and (10), and the 
decomposition is summarized in Table 3. 

INSERT TABLE 3 HERE 

The results indicate that of the total effects of participation on 
performance, the effect through motivation accounts for only a small 
proportion, the majority appearing to be direct. The lack of explanatory 
power of motivation as a mediator of the effects of participation was, of 
course, first hinted at in Table 1, where the zero-order correlation between 
the two was found to be insignificant. It is, nonetheless, premature to 
conclude that the bulk of the effects of participation on performance are 
necessarily direct. Other variables, operating like motivation but 
unmeasured in this study, could account for some or all of what in the study 
has been accounted for as an apparent direct effect. 
Further Analysis and Interpretation 

In the aggregate analysis, participation and motivation are not 
significantly associated with one another. To examine this finding further, 
the associations between participation and the components of the expectancy 
model were explored. The results of the analysis are shown in Table 4. 



-13- 



INSERT TABLE 4 HERE 



In the first column the simple correlation coefficients between 
participation and the nine extrinsic valences are shown. Four of the nine 
are negative and five are positive. There is no a priori reason to suppose 
that extrinsic valences should be influenced by the degree of participation, 
and this is borne out. However, the P„'s display an interesting pattern 
in relation to participation; the coefficients are shown in the second 
column. While only five of the nine coefficients are positive, three are 
significant, namely, the probability of pay raise, high pay and promotion. 
The third column shows the correlation coefficients between participation 
and the products of the ^ j' s and the extrinsic valences. It seems as if 
participation, largely through its effect on the P^'s, enhances the 
contribution of the extrinsic rewards to motivation - particularly those 
rewards within the official power of the organization to bestow. 

An interpretation of this is that participation serves to legitimize the 
budget as a basis for performance evaluation and contingent administration 
of organizational rewards. Such a conclusion is consistent with previous 
findings (Brownell, 1982b), to the effect that a "budget-constrained" style 
of evaluation was appropriate in circumstances of high participation in 
budget-setting; conversely, managers were found to respond poorly to 
participation when the budget was not used as a salient basis for evaluation. 

Column's 4 and 5 show the correlation coefficients between participation 

and the intrinsic valences, the eight IV 's and the eight IV, 's. For 

a D 

both of these groups, six of eight of the coefficients are negative (p < 

-14- 



0.11, using a binomial test); overall, 12 of 16 correlations between 
participation and intrinsic valences are negative (p < 0.03). Contrary to 
the belief that participation is likely to enhance goal-commitment by 
increasing the level of ego-involvement associated with the pursuit of 
self-set goals, these results suggest that it appears to be acting in the 
opposite manner. Indeed, from an intrinsic perspective, participation 
appears to be associated with significant devaluation of the task and 
reduction of the satisfaction derived from goal-accomplishment. In line 
with the previous suggestions (Staw [1980] and Kruglanski [1978]), 
strengthening of the instrumentality between goal-accomplishment and 
extrinsic rewards appears to diminish, in some degree, the intrinsic 
valences. 

The correlations between participation and the three measures of P, 
(the probability that goal-directed effort will lead to goal accomplishment) 
were all found to be positive. Participation correlates with the overall 
measure of P-, at 0.18 (p < 0.08). Two explanations of this would be 
plausible. First, perhaps participation acts to strengthen goal commitment, 
effort, and therefore the perceived probability of goal-achievement. There 
is considerable evidence from the organization! behavior literature (see 
Locke et al., 1981) that the intrinsic value of goal accomplishment tends to 
increase as the level of goal difficulty increases. Indeed, this mechanism 
is central to the notion of goal-setting and motivation. In the current 
study, however, the negative association between participation and the 
intrinsic valences relating to goal-accomplishment is at odds with this 
explanation. A second explanation is that participation may provide an 
opportunity to negotiate easier goals; that is, budget slack may be 
introduced by participation (Schiff and Lewin, 1970; Onsi, 1973). This 
would be consistent with the observed negative association of participation 

-15- 



with the IV 's, since achieving an easier goal would be likely to lead to 
less intrinsic satisfaction. Moreover, since participation appears to be 
connected with the use of the budget to evaluate performance as a basis for 
bestowing organizational rewards, it would be perfectly rational for 
managers to perceive it to be in their self-interest to negotiate as low a 
budget as possible (Lowe and Shaw; 1968). 

The preceding interpretation of the research findings raises important 
questions about the benefits of participation in budget-setting. 
Nonetheless, the study does indicate a significant positive relationship 
between participation and the overall measure of performance. To explore 
this further, each of the eight sub-dimensions of performance was correlated 
with participation, and the results are shown in Table 3. 



INSERT TABLE 5 HERE 



All eight correlations are positive, and significant (p < 0.05). An 
examination of the pattern among the coefficients suggests that the 
dimensions of managerial performance which are most strongly associated with 
participation are precisely those which might be expected to be strengthened 
by judicious use of a budget as a managerial tool, in particular planning, 
investigating and evaluating. 
Limitations and Conclusions 

The aim of the study was to assess whether, compared with a 
"direct-effects" model, an "indirect-effects" model linking participation 
and performance has the potential to add to our understanding of the 
consequences of participation. In the interests of parsimony, a single 

-16- 



variable, motivation, was included as intervening between participation and 
performance. The results of the study show that the indirect path through 
motivation contributes relatively little to an explanation of the observed 
association between participation and performance. This evidence, however, 
is insufficient grounds for abandoning the "indirect-effects" model. Other 
intervening variables could enter the model. For example, ability and role 
clarity have been suggested as co-determinants, with motivation, of 
performance (Porter and Lawler, 1968; Lawler, 1971). Further research is 
necessary to resolve this matter. 

The form of the expectancy model of motivation adopted in the study also 
requires further research and possible refinement. For example, Staw (1977) 
offers a rationale for recognizing the possibility of extrinsic valences 
being associated with goal-directed behavior, rather than simply with 
goal-accomplishment. Moreover, multiple extrinsic valences enter into the 
equation additively, whereas both the intrinsic valences enter the equation 
as single mean values. This has implications for the relative weightings 
accorded extrinsic and intrinsic valences respectively in the calculation of 
motivation. 

Then there is the question of the appropriateness of the measure of 
performance in a research study such as this one. The criterion variable of 
ultimate concern is an organization's creation of profit potential and the 
realization of this through efficient operations. However, budgeting is 
primarily concerned with the regulation of managerial work within an 
organization. In this limited context, the appropriate criterion variable 
of direct interest is managerial performance, even if the connection between 
managerial performance and organizational effectiveness remains a broader 
concern. This still leaves the issue of the reliability of self-ratings of 
performance, compared with superior, peer or subordinate ratings. While 

-17- 



self-ratings have been shown to exhibit leniency error, provided the error 
is not systematic among the respondents in a manner which is collinear with 
any of the independent variables, the research findings will be unaffected. 
Furthermore, Kavanagh et al. (1971) have suggested that self-ratings provide 
greater discrimination among dimensions of performance than do other sources 
of rating, and may therefore be more reliable in analyzing the components of 
performance which contribute to the overall assessment. Having said this, 
however, exhortations (e.g. Steers, 1977) to devote more research effort to 
the development of better techniques for measuring performance are clearly 
valid. 

Finally, there is the issue of causality and the direction in which 
effects among variables in the model proceed. The analysis done in the 
study does not permit any inference about the causalities; these can only be 
constructed from supporting theory. In this study, it is implied that 
perceived participation in budget-setting may cause higher levels of 
motivation, which in turn may cause higher levels of performance. But, in a 
dynamic, inter-temporal context a rationale could be constructed to argue 
for a reverse chain of causality - i.e. high performance leading to high 
motivation leading to a perception (and indeed perhaps a reality) of high 
participation in budget-setting. For example, it is entirely possible that 
participation might be viewed as a luxury affordable only to organizational 
units already performing satisfactorily. 

i^ven recognizing the limitations of the study, the findings are 
potentially of significance in the design of control systems. Participation 
is a costly control strategy, since it consumes managerial resources. The 
findings of the study indicate that the control system cost may be 
compensated by improved managerial performance. But, on the other hand, the 
findings also indicate some latent costs in the participation process, 

-18- 



arising in two ways. First, some potential performance may be being 
sacrificed through the creation of budgetary slack. And secondly, costly 
organizational rewards, contingent on the achievement of budgets, may be 
supplanting intrinsic rewards. These latter rewards could be viewed as 
being costless to the organization; stated even more strongly, their 
suppression could induce hidden costs through, for example, diminished 
creativity within the organization. 

It is precisely because of these hidden consequences that the 
"indirect-effects" model is potentially of considerable practical, as well 
as theoretical, interest. A greater understanding of the mechanisms through 
which participation affects performance should provide management with a 
basis for designing the participation process in such a way as to capture 
all the benefits, and to drive out the latent costs which the results of 
this study have indicated. 



-19- 



TABLE 1 
Zero-Order Correlations Between Variables 

Participation(Xi)/Performance(X3) , r = 0.369, p<O.Ol 
Participation(X]^)/Motivation(X2) , r = 0.139, n.s. 
Motivation(X2)/Perforroance(X3) , r = 0.248, p<O.Ol 

TABLE 2 
Calculation of Path Coefficients P3-]^ and P32 



Standard 
Coefficient Value Error t 



Intercept 


0.000 


0.088 


0.00 


n.s. 


P31 


0.341 


0.089 


3.81 


<0.01 


P32 


0.201 


0.089 


2.25 


<0.05 



r2 = 0.176, F2^i05 = 11.20, p <0.01 







TABLE 


3 






De^ 


com 


iposition of Total 


Effects in 


Mod 


el 


Linkage 




Direct (=p) 


Indirect 




Total (=r) 


X1/X2 




0.139 







0.139 


X1/X3 




0.341 


0.028 




0.369 


X2/X3 




0.201 


0.047 




0.248 



-20- 



TABLE 4 
Correlations between Participation and 
the Elements of the Expectancy Model 



Outcome* 


EV. 

1 


^2i 


^2i^^ 


IV 
a 


'\ 


1 


.143 


.232 


.232 


.025 


.041 


2 


.075 


.196 


.159 


-.033 


-.072 


3 


.060 


-.052 


.037 


-.042 


.086 


4 


-.141 


-.049 


-.106 


-.136 


-.112 


5 


-.201 


-.097 


-.136 


-.016 


-.058 


6 


-.010 


.104 


.001 


-.133 


-.044 


7 


.049 


-.201 


.057 


.011 


-.098 


8 


-.024 


.070 


.061 


-.042 


-.155 


9 


.128 


.192 


.206 


N/A 


N/A 



* The numbered outcomes are listed in Appendix A. 

N/A Not Applicable 

.191 > r > .160, p < 0.10 

.248 > r > .191, p < 0.05 

r > .248, p < 0.01 



-21- 



TABLE 5 
Correlations between Participation and 
the Eight Sub-Dimensions of Performance 



Planning 


0.297 


Investigating 


0.219 


Coordinating 


0.209 


Evaluating 


0.30A 



Supervising 


0.201 


Staffing 


0.284 


Negotiating 


0.217 


Representing 


0.174 



-22- 



Appendix A 



List of Outcomes 



Eight intrinsic and nine extrinsic outcomes were used in this study. 



Extrinsic Intrinsic 

1. Pay Raise 1. Personal growth and development 

2. High Pay 2. Setting higher standards for yourself 

3. Respect from boss 3. Giving help to others 

4. Respect from other employees 4, Time at work passing fast 

5. Receiving more compliments 5. Feelings of security ' 

6. Greater chances for independent 6. Setting higher standards for others 
thought and action 

7. Fewer chances to make friends 7. Feelings of accomplishment 

8. Special reward or recognition 8. Being tired 

9. Promotion 



-23- 



Appendix B 

The solution to equation (3) can be derived through the use of 
instrumental variables. As suggested earlier, X, and X„ serve as 
suitable instruments since they are assumed uncorrelated with R . 

Multiplying both sides of (3) by X, and then by X„ gives: 

hh = P3l4 ^ P32V2 ^ ^3v\K ^'^ 

'"' hh - ^31^1^2-^ P32^2 ^ P3v^2\ ^^^^ 

Taking the expected value of each of (i) and (ii) gives 

r^3 = P31 + P32ri2 ^^^^^ 

^^23 = P31^12 + P32 ^^^^ 

(iii) and (iv) follow from (i) and (ii) since, for standardized 

variables, 

(a) E(X.X.) = r. . 

^'^^ (b) E(X^) = 1. 

1 

The terms involving R disappear since 

E^^i^v) = ^X.R = 0- 
1 V 

(iii) and (iv) represent a system of two equations in two unknowns 
(poi and Pon)« Solving (iii) and (iv) simultaneously gives 

_ ^^13 "^ ^^12^23 (v) 

P3I \ 2 

1- r^2 



P 



^ ^23 "^ ^12^13 (vi) 

32 , 2 
1 - r^2 



-24- 



Substituting the values from Table 1 for the r's in (v) and (vi) gives 
p, = 0.341, and ^^^ " 0*201, values identical to those shown in Table 2. 



■25- 



Footnotes 

1. An internally controlled individual attributes the outcomes of his o\^m 
actions to himself, while an externally controlled individual tends to 
attribute these outcomes to chance, luck, or fate. See Rotter [1966] 
for details of this variable, together with the instrument used to 
measure it. 

2. Of course, we do not intend to imply, by its choice as a single 
intervening variable, that motivation is the only candidate for 
inclusion. 

3. These raw scores were reversed and rescaled by subtracting five from all 
scores. As a result of this procedure, "neutral" responses score zero, 
while responses in the "desirable" direction score positively (one to 
four) and responses in the "undesirable" direction score negatively 
(minus one to minus four). 

4. The dimensions were planning, investigating, coordinating, evaluating, 
supervising, staffing, negotiating and representing. 

5. This procedure is also used to test the suitability of more parsimonious 
models which exclude one or more linkages. In general, the assessment 
of suitability is based on whether the original matrix of 
intercorrelations among the variables in the model can be reproduced by 
a more parsimonious model. For elaboration, see Land (1969). 

6. As previously mentioned, it was not necessary to solve equation (2) 
since P2i is equivalent to r]^2> the zero-order correlation between 
participation and motivation. 

7. The equivalence of the coefficients derived here with those resulting 
from the instrumental variable procedure is demonstrated in Appendix B. 



-26- 



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-29- 



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